Intelligent Service Management and Process Control Using Policy-Based Automation and Predefined Task Templates

ABSTRACT

Mechanisms are provided for dynamically determining one or more automation levels for tasks of a workflow. The mechanisms receive a workflow from a source component and receiving context and state information for an environment in which the workflow is to be performed. One or more tasks and associated task attributes are identified in the workflow and applying one or more automation rules to the context and state information and the task attributes to generate one or more automation level settings from the one or more tasks. The one or more tasks are performed in the environment in accordance with the one or more automation level settings. The automation level settings specify a degree of automation to be used when performing the one or more tasks.

BACKGROUND

The present application relates generally to an improved data processingapparatus and method and more specifically to mechanisms for providingintelligent service management and process control using policy-basedautomation.

Today's society increasingly utilizes computer control mechanisms forcontrolling various systems that human beings rely upon. These computercontrol mechanisms must ensure delivery of reliable service and protectfrom unintended consequences and unwise system behavior that mayendanger the public.

Complete computer control of these systems provides a level ofefficiency and accuracy that typically cannot be obtained from manual,human based control. However, humans are reluctant to give up completecontrol to such computer control systems since, no matter how welldevised the computer control system may be, there is always thepossibility that it may behave in an unintended manner or, whilebehaving in a proper manner according to its programming, the particularconditions or situation may cause the proper behavior of the computercontrol system to generate unintended consequences. Thus, it isdifficult to determine a proper balance between automated computercontrol and human based manual control.

SUMMARY

In one illustrative embodiment, a method, in a data processing system,is provided for dynamically determining one or more automation levelsfor tasks of a workflow. The method comprises receiving a workflow froma source component and receiving context and state information for anenvironment in which the workflow is to be performed. The method furthercomprises identifying one or more tasks and associated task attributesin the workflow and applying one or more automation rules to the contextand state information and the task attributes to generate one or moreautomation level settings from the one or more tasks. The method alsocomprises performing the one or more tasks in the environment inaccordance with the one or more automation level settings. Theautomation level settings specify a degree of automation to be used whenperforming the one or more tasks.

In other illustrative embodiments, a computer program product comprisinga computer useable or readable medium having a computer readable programis provided. The computer readable program, when executed on a computingdevice, causes the computing device to perform various ones of, andcombinations of, the operations outlined above with regard to the methodillustrative embodiment,

In yet another illustrative embodiment, a system/apparatus is provided.The system/apparatus may comprise one or more processors and a memorycoupled to the one or more processors. The memory may compriseinstructions which, when executed by the one or more processors, causethe one or more processors to perform various ones of, and combinationsof, the operations outlined above with regard to the method illustrativeembodiment.

These and other features and advantages of the present invention will bedescribed in, or will become apparent to those of ordinary skill in theart in view of, the following detailed description of the exampleembodiments of the present invention.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The invention, as well as a preferred mode of use and further objectivesand advantages thereof, will best be understood by reference to thefollowing detailed description of illustrative embodiments when read inconjunction with the accompanying drawings, wherein:

FIG. 1 is an example diagram of a distributed data processing system inwhich aspects of the illustrative embodiments may be implemented;

FIG. 2 is an example block diagram of a computing device in whichaspects of the illustrative embodiments may be implemented;

FIG. 3 is an example block diagram illustrating the primary operationalelements of a flexible automation workflow management engine inaccordance with the illustrative embodiments;

FIG. 4 is an example diagram illustrating the operation of the elementsof FIG. 3 with regard to a workload submitted from an originatingcomponent in accordance with one illustrative embodiment;

FIG. 5 is an example diagram of a workflow upon which the flexibleautomation workflow management engines of the illustrative embodimentsmay operate; and

FIG. 6 is a flowchart outlining an example operation for performing aflexible automation determination for a workflow in accordance with oneillustrative embodiment.

DETAILED DESCRIPTION

The illustrative embodiments provide mechanisms for providingintelligent service management and process control using policy-basedautomation. The mechanisms of the illustrative embodiments operate tocontrol a balance between human intervention and automated computercontrol based on policy-based rules and dynamic conditions. As a result,the efficiency of computer control is achieved as much as possible whileminimizing risks of unintended consequences or behavior that mayendanger human beings.

Operational service management or process control can be thought of asworkflows of operator driven or automated tasks. These workflows maysupport business processes or services, information technology services,industrial control processes, etc. The workflows generally consist ofinstrumentation, data collection, data analysis, reporting, andmanagement operations.

Management operations in a workflow are often driven by human operatorreaction following an alert from the computer system. Managementoperations may also be automated when the range of operating conditionsand associated actions can be fully defined in the computer system.Fully automated management operations are predicated on the ability toforego the intervening manual checkpoints between chained automatedtransactions.

A key concern for fully automated management is that automation withoutintervening manual checkpoints has the potential to introduce errors andadverse consequences. Depending on the system being controlled, fullyautomated self-management of the system can be unwise or even deadly.For example, fully automated control of aircraft control towers,hazardous materials transports, or other inherently dangerous systemswould be unwise and can potentially endanger the public. However,complete human control introduces possible sources of error and isextremely inefficient when compared to computer control systems.

Whether and when to execute manual or automated management operations isa critical operational decision in modern systems. For example,International Business Machines Corporation of Armonk, N.Y., hasintroduced an initiative for increasing computer automation of systemsused in society referred to as “Smarter Planet.” Smarter Planet is aninitiative that examines ways to apply information technology to improveefficiency and effectiveness of infrastructure systems and processesthat support and sustain society. Some examples of Smarter Planetrelated systems are: water management systems, smart electricdistribution grids, traffic flow systems and energy efficient buildings.These and related uses for information technology have the potential tobe larger in scale, impact and risk than information technology used fora single business enterprise, government agency or user community.

Improvements related to Smarter Planet may come when repetitive worktasks are automated. The term “workflow” is often applied to a sequenceof tasks. A workflow may be seen as any abstraction of real work, thatis, a depiction of a sequence of operations, that represents the work ofa person, or a group of persons. There are many instances of computingsystems that facilitate workflow. Some embodiments are: systems thatserve instructions that humans may read and follow and acknowledgecompletion of tasks, systems that can be configured to performrepetitive actions, as in numerical control machines, or systems thatautomate the management of information technology systems. TheInformation Technology Infrastructure Library, or ITIL standard,provides an example of a catalog of processes and workflows associatedwith management of information systems and services.

The decision of whether a workflow is acted out by a human or isperformed programmatically by a computer system is one that must takeinto consideration a large range of factors. For example, these factorsmay include a system content, operating conditions, applicable threats,operational risks, and processes and assets being controlled. Theability for the system designer, the system installer, the systemadministrator, or the service user to match the level of automation withthe business or technical risks and dynamic operating conditions isreferred to herein as “flexible automation” and is the focus of themechanisms of the illustrative embodiments.

Flexible automation in accordance with the illustrative embodimentsprovides the system designer, system installer, service administrator,and/or service user to control the automation level of tasks within aworkflow that operates on target systems or devices based on automationrules defined by automation policies. A process script can be carriedout in several ways, whether by entirely manual techniques, by entirelyautomated techniques, or using varying steps of manual, assisted, and/orfully automated techniques. Flexible automation, in accordance with theillustrative embodiments, provides the programmable mechanism (controlpoint) that selects the most appropriate automation level for thedesired task based on information about the operating environment,business state and conditions, information technology operating stateand conditions, business and/or information technology operating rules,business and/or information technology operating risks, business and/orinformation technology operating objectives, etc. Flexible automationprovides for the following possibilities: (1) to maintain a prescribed,or default, automation level for the desired task; (2) to increase thelevel of automation for the desired task in order to gain efficienciesor productivity; and (3) to reduce the level of automation for thedesired task (including escalating the task to human intervention), inorder to mediate the affects or consequences of the tasks in relation tothe business and technical objectives.

Flexible automation involves delegation. Delegation affects the flow oftasks in a workflow and whether the workflow can be completed withautomation or whether human interaction is warranted. In the context ofthe description of the illustrative embodiments, the term “delegation”relates to the ability of a system designer, a system installer, aservice administrator, or a service user, to assert control (nodelegation) versus to assign control (delegation) to another person orprogram entity. A key corollary to delegation is “escalation.”Escalation also affects the flow of tasks in a workflow. In the contextof the description of the illustrative embodiments, the term“escalation” relates to the ability of an owning person or programentity to relinquish ownership or defer to a higher authority. A systemthat implements the flexible automation mechanisms of the illustrativeembodiments provides for both “delegation” and “escalation” to achieveintelligent service management. This means that automation for servicemanagement needs to be controlled in such a way that decisions are“delegated” to software as appropriate, and some “delegated” actions mayneed to be “escalated” to the attention of a human when warranted.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in any one or more computer readablemedium(s) having computer usable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CDROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, in abaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device,

Computer code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, radio frequency (RF), etc., or anysuitable combination thereof.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java™ Smalltalk™, C++, or the like, and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer, or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider),

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to the illustrativeembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions thatimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus, or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

Thus, the illustrative embodiments may be utilized in many differenttypes of data processing environments. In order to provide a context forthe description of the specific elements and functionality of theillustrative embodiments, FIGS. 1 and 2 are provided hereafter asexample environments in which aspects of the illustrative embodimentsmay be implemented. It should be appreciated that FIGS. 1 and 2 are onlyexamples and are not intended to assert or imply any limitation withregard to the environments in which aspects or embodiments of thepresent invention may be implemented. Many modifications to the depictedenvironments may be made without departing from the spirit and scope ofthe present invention.

FIG. 1 depicts a pictorial representation of an example distributed dataprocessing system in which aspects of the illustrative embodiments maybe implemented. Distributed data processing system 100 may include anetwork of computers in which aspects of the illustrative embodimentsmay be implemented. The distributed data processing system 100 containsat least one network 102, which is the medium used to providecommunication links between various devices and computers connectedtogether within distributed data processing system 100. The network 102may include connections, such as wire, wireless communication links, orfiber optic cables.

In the depicted example, server 104 and server 106 are connected tonetwork 102 along with storage unit 108. In addition, clients 110, 112,and 114 are also connected to network 102. These clients 110, 112, and114 may be, for example, personal computers, network computers, or thelike. In the depicted example, server 104 provides data, such as bootfiles, operating system images, and applications to the clients 110,112, and 114. Clients 110, 112, and 114 are clients to server 104 in thedepicted example. The distributed data processing system 100 may furtherinclude other devices 120-126 either coupled to the network 102 directlyor via one or more other computing devices, such as clients 110, 112,and 114. These other devices 120-126 may be of various types includingvarious physical devices 120, smart devices 122, sensors 124, actuators126, and the like. Examples of these types of devices include cameras,temperature sensors, fluid flow sensors, valves, and the like.Essentially, any device or system that may perform tasks as part of aworkflow may be used without departing from the spirit and scope of theillustrative embodiments. Distributed data processing system 100 mayinclude additional servers, clients, and other devices not shown.

In the depicted example, distributed data processing system 100 is theInternet with network 102 representing a worldwide collection ofnetworks and gateways that use the Transmission ControlProtocol/Internet Protocol (TCP/IP) suite of protocols to communicatewith one another. At the heart of the Internet is a backbone ofhigh-speed data communication lines between major nodes or hostcomputers, consisting of thousands of commercial, governmental,educational and other computer systems that route data and messages. Ofcourse, the distributed data processing system 100 may also beimplemented to include a number of different types of networks, such asfor example, an intranet, a local area network (LAN), a wide areanetwork (WAN), or the like. As stated above, FIG. 1 is intended as anexample, not as an architectural limitation for different embodiments ofthe present invention, and therefore, the particular elements shown inFIG. 1 should not be considered limiting with regard to the environmentsin which the illustrative embodiments of the present invention may beimplemented.

FIG. 2 is a block diagram of an example data processing system in whichaspects of the illustrative embodiments may be implemented. Dataprocessing system 200 is an example of a computer, such as client 110 inFIG. 1, in which computer usable code or instructions implementing theprocesses for illustrative embodiments of the present invention may belocated.

In the depicted example, data processing system 200 employs a hubarchitecture including north bridge and memory controller hub (NB/MCH)202 and south bridge and input/output (I/O) controller hub (SB/ICH) 204.Processing unit 206, main memory 208, and graphics processor 210 areconnected to NB/MCH 202, Graphics processor 210 may be connected toNB/MCH 202 through an accelerated graphics port (AGP).

In the depicted example, local area network (LAN) adapter 212 connectsto SB/ICH 204. Audio adapter 216, keyboard and mouse adapter 220, modem222, read only memory (ROM) 224, hard disk drive (HDD) 226, CD-ROM drive230, universal serial bus (USB) ports and other communication ports 232,and PCI/PCIe devices 234 connect to SB/ICH 204 through bus 238 and bus240. PCI/PCIe devices may include, for example, Ethernet adapters,add-in cards, and PC cards for notebook computers. PCI uses a card buscontroller, while PCIe does not. ROM 224 may be, for example, a flashbasic input/output system (BIOS).

HDD 226 and CD-ROM drive 230 connect to SB/ICH 204 through bus 240. HDD226 and CD-ROM drive 230 may use, for example, an integrated driveelectronics (IDE) or serial advanced technology attachment (SATA)interface. Super I/O (SIO) device 236 may be connected to SB/ICH 204.

An operating system runs on processing unit 206. The operating systemcoordinates and provides control of various components within the dataprocessing system 200 in FIG. 2. As a client, the operating system maybe a commercially available operating system such as Microsoft® Windows7®. An object-oriented programming system, such as the Java™ programmingsystem, may run in conjunction with the operating system and providescalls to the operating system from Java™ programs or applicationsexecuting on data processing system 200.

As a server, data processing system 200 may be, for example, an IBM®eServer™ System P® computer system, running the Advanced InteractiveExecutive (AIX®) operating system or the LINUX® operating system. Dataprocessing system 200 may be a symmetric multiprocessor (SMP) systemincluding a plurality of processors in processing unit 206.Alternatively, a single processor system may be employed.

Instructions for the operating system, the object-oriented programmingsystem, and applications or programs are located on storage devices,such as HDD 226, and may be loaded into main memory 208 for execution byprocessing unit 206. The processes for illustrative embodiments of thepresent invention may be performed by processing unit 206 using computerusable program code, which may be located in a memory such as, forexample, main memory 208, ROM 224, or in one or more peripheral devices226 and 230, for example.

A bus system, such as bus 238 or bus 240 as shown in FIG. 2, may becomprised of one or more buses. Of course, the bus system may beimplemented using any type of communication fabric or architecture thatprovides for a transfer of data between different components or devicesattached to the fabric or architecture. A communication unit, such asmodem 222 or network adapter 212 of FIG. 2, may include one or moredevices used to transmit and receive data. A memory may be, for example,main memory 208, ROM 224, or a cache such as found in NB/MCH 202 in FIG.2.

Those of ordinary skill in the art will appreciate that the hardware inFIGS. 1 and 2 may vary depending on the implementation. Other internalhardware or peripheral devices, such as flash memory, equivalentnon-volatile memory, or optical disk drives and the like, may be used inaddition to or in place of the hardware depicted in FIGS. 1 and 2. Also,the processes of the illustrative embodiments may be applied to amultiprocessor data processing system, other than the SMP systemmentioned previously, without departing from the spirit and scope of thepresent invention.

Moreover, the data processing system 200 may take the form of any of anumber of different data processing systems including client computingdevices, server computing devices, a tablet computer, laptop computer,telephone or other communication device, a personal digital assistant(PDA), or the like. In some illustrative examples, data processingsystem 200 may be a portable computing device that is configured withflash memory to provide non-volatile memory for storing operating systemfiles and/or user-generated data, for example. Essentially, dataprocessing system 200 may be any known or later developed dataprocessing system without architectural limitation.

Moreover, aspects of the mechanisms of the illustrative embodiments maybe implemented in, or in association with, other physical devices 120,smart devices 122, sensors 124, actuators 126, or the like. These otherphysical devices 120, smart devices 122, sensors 124, actuators 126, andthe like may be coupled with or otherwise associated with a dataprocessing system or computing device or may be able to be accesseddirectly via one or more data networks. These physical devices 120,smart devices 122, sensors 124, actuators 126, and the like, may providemetric data for use in determining a level of automation to be utilizedas well as may be directly or indirectly (e.g., through anothercomputing device) controlled based on a set level of automation for atask to be performed by the physical device 120, smart device 122,sensor 124, actuator 126, or the like, as part of a workflow.

With reference again to FIG. 1, workflows, which may be comprised of aplurality of different processes, tasks, and the like, may be submittedby various computing devices within the distributed data processingsystem 100 and the workflow management operations may be performed byone or more of the servers 104, 106 in the data processing system 100.As part of these workflow management operations the servers 104, 106 mayperform flexible automation operations in accordance with theillustrative embodiments herein to control the level of automation usedto implement the workflows.

FIG. 3 is an example block diagram illustrating the primary operationalelements of a flexible automation workflow management engine inaccordance with the illustrative embodiments. The elements shown in FIG.3 may be implemented as software, hardware, or any combination ofsoftware and hardware. In one illustrative embodiment, the elements ofFIG. 3 are implemented as software instructions, loaded into one or morememories or other types of storage devices, and executed by one or moreprocessors of one or more data processing devices/systems. In otherillustrative embodiments, one or more of the elements of FIG. 3 may beimplemented in circuitry, such as firmware for example.

As shown in FIG. 3, the flexible automation workflow management engine300 comprises a controller 310, an interface 320, a task sequencer 330,an automation evaluation exit (AEE) module 340, an automation levelevaluator (ALE) module 350, and a rules database 360. The controller 310controls the overall operation of the flexible automation workflowmanagement engine 300 and orchestrates the operation of the otherelements 320-360. The interface 320 provides a communication pathwaythrough which data may be received and sent. For example, the interface320 may receive workflows from source components 305, e.g.,applications, operating systems, workflow or project management systems,or the like, executing on client computing devices, server computingdevices, or the like. The flexible automation workflow management engine300 may operate on the received workflows and determine various levelsof automation for various processes within the workflow. As a result, acorresponding control output may be generated and sent back to thesource component to control a level of automation implemented by thesource component 305 and its associated components, e.g., otherapplications, systems, computing devices, physical devices, sensors,actuators, smart devices, and the like. Alternatively, components forimplementing the various processes of the workflow may be directlycontrolled by the flexible automation workflow management engine 300based on the results of analysis of the workflow by sending appropriatecommands directly to these components to cause them to operate inaccordance with the level of automation associated with the processes.

Each process in the processes of a workflow may have a different levelof automation from one or more other processes of the workflow. Thus,for example, a first process in the workflow may have a different levelof automation than that of a second process in the workflow, e.g., thefirst process is a fully manual or semi-manual process while the secondprocess is a fully automated process. The determination of theappropriate level of automation may be determined based on an analysisof the particular process or task to be performed in relation topre-established automation rules.

Consider, as one example, a workflow for updating the software that isinstalled in a computing system. An information system managementworkflow system could be configured to recognize an input event andcommand, and carry out the sequence of steps required to update thesoftware on a target computing system, such as source component 305,target system 370, or other target component in the target environment380. The steps might include: gathering information about the targetsystem, gathering information about the software update, enabling thetransfer of software to the target system, invoking the commands toready the system for update and checking for completion, invoking thecommands to apply the update and checking for completion, and finally,performing post processing for completed process, or cleanup in theevent that errors have occurred. Flexible operation may be used tooptimize the activity of updating software in a computing system whereinformation about the systems involved, the software involved, and otheraspects of the operating environment could introduce variability in theworkflow. For example, if the target system is identified as “test”environment, then the update could proceed with full automation. If onthe other hand the system is identified as “production” environment andis currently “online”, it would be prudent to defer the installationuntil the system is “offline”. There are potentially a wide range ofsystem attributes, system states and even time-of-day or day-of-weekvariables that could contribute to decisions about whether and how tocomplete the desired workflow.

Returning to FIG. 3, the task sequencer 330 receives a workflow from asource component 305 and performs various operations for scheduling theexecution of tasks or processes of the workflow. The term “tasksequencer” is a generalized term given to a component of a workflowsystem that invokes sequences and initiates the tasks in a workflow.Task sequencers are generally known in the art and thus, a detaileddescription of the sequencing operations performed by task sequencers isnot provided herein. With regard to the illustrative embodiments,however, the task sequencer 330 of the illustrative embodiments ismodified and configured to operate in conjunction with an automationevaluation exit (AEE) module 340 and automation level evaluator (ALE)350 as described hereafter. While the task sequencer 330 is shown as acomponent of the flexible automation workflow management engine 300, itshould be appreciated that the task sequencer 330 may in fact beseparate from the flexible automation workflow management engine 300 andmay in fact be part of a separate workflow management system but isconfigured to interface with the AEE 340 and/or ALE 350, such as via anapplication programming interface (API) or other appropriate interfacemechanism.

The source component 305 may submit a work order to a workflowmanagement system which maps the work order to a workflow. The workflowmay be submitted by the workflow management system to the task sequencer330 which separates the workflow into its constituent processes or tasksand submits work orders for each of the individual constituent processesor tasks to the AEE 340 to operate upon. The breaking down of theworkflow into individual processes or tasks may involve the use ofpredefined process or task templates. That is, the task sequencer 330may compare processes or tasks of a workflow to predefined templates,determine the template associated with each process or task in theworkflow, and generate a set of process/task templates to be used todefine the workflow within the task sequencer 330. These templates maythen be converted to work orders that conform with the process/tasktemplate. The work orders are then provided to the ALE 350 to determinean appropriate level of automation for the corresponding work order.

The AEE 340 invokes the ALE 350 to examine the work order, its contextinformation, and any other available information regarding the currentstate of the environment in which the process or task is to beperformed. In one illustrative embodiment, this context information andother available information comprises the current state of theenvironmental variables, and the like, of the source component 305and/or the system(s) in which the source component 305 is present orwith which it operates, e.g., congestion levels, available bandwidth,processor utilization, memory utilization, personnel availability,storage availability, equipment availability, etc. This information maybe in the form of fixed parameters that are coded in the work order,information that is gathered from the system at the time of execution,or the like. The set of context information and state informationgathered and utilized is implementation specific and may encompass anycontext/state information that is able to be obtained from the sourcecomponent 305 and the system(s) associated with the source component305. The context/state information to be utilized may be selected so asto provide sufficient information for determining a level of riskassociated with different levels of automation without being socomprehensive as to slow the mechanisms to a point where they create toomuch delay in the overall operation of the flexible automation workflowmanagement engine 300.

One attribute of the work orders generated by the task sequencer 330 isan automation level. The automation level may or may not have been setby the source component 305 submitting the workflow. If not explicitlyset by the source component 305 submitting the workflow, then thisautomation level may be given a default value. This automation levelattribute of the work order may be dynamically modified, e.g.,downgraded or upgraded (escalated) based on the application ofautomation rules from the rules database 360 to the work order and thecontext/state information. For purposes of the present description, as aconvention, it will be assumed that a downgrade of the automation levelrefers to setting the automation level attribute to a value that iscloser to full manual execution of the corresponding process/task.Similarly, an upgrade of the automation level refers to setting theautomation level attribute to a value that is closer to full automatedexecution of the corresponding process/task.

Various automation rules from the rules database 360 may be applied bythe ALE 350 to the work order, the context information, and the currentstate information, to analyze the work order and the context/stateinformation and determine an appropriate level of automation for thecorresponding process/task taking into consideration the current dynamiccontext/state of the environment in which the process/task is to beexecuted. The application of these automation rules to the work orderand the context/status information results in a determination as towhether the automation level attribute of the work order should bemaintained at its current value, upgraded, or downgraded and by howmuch, if any, the automation level attribute of the work order should beupgraded/downgraded.

The particular application of the rules to particular portions of thework order and context/status information is implementation specific andmay take many different forms. The following are examples of the typesof rules that may be used with the mechanisms of the illustrativeembodiments:

A) maintain, upgrade, or downgrade the automation level attribute basedon the productivity of the user role associated with the process/task;

B) maintain, upgrade, or downgrade the automation level attribute basedon the context of the source component submitting the workflow;

C) maintain, upgrade, or downgrade the automation level attribute basedon an alignment of the process/task with defined business rules orrisks;

D) maintain, upgrade, or downgrade the automation level attribute basedon a determined impact of the process/task on other elements/objects ofthe source component and/or related system(s) and components; and

E) maintain, upgrade, or downgrade the automation level attribute basedon an alignment of the process/task with operating conditions of thesource component 305 and/or related system(s) and components.

The automation rules may be specified in terms of automation policiesthat are stored in association with the ALE 350. Preferably, theautomation policies/rules are defined to promote self-management of theworkflow. In the context of the present description, self-managementrefers to the ability to reduce the number of units of work required toperform the particular processes/tasks of the workflow, reduce theamount of time required to complete the processes/tasks of the workflow,and adapt the workflow to align with business and technical needs asidentified by business rules and current context/state information.

These automation policies/rules may have various forms includingdeclarative form, simple condition form, stateful conditional form, orgoal based form. A declarative form of policy/rule declares anautomation level attribute setting without specifying conditionals. Forexample, a declarative policy/rule may be of the type “All operatorswill use manual automation (M)” or “All operators can select manual (M),semi-automated (S), or fully automated (A).”

A simple conditional policy/rule may take the form of “if <condition>then <action>.” An example of such a simple conditional policy/rule is“if (mode) then (task); Production, (M); Test, (A)” which sets theautomation level to manual if the mode is a production mode andautomated if the mode is a test mode. Another example conditionalpolicy/rule is “if (role) then (task); Operator, (S); Administrator,(M); Analyst, <any>; User, <none>” which sets the automation level tovarious settings of semi-automated, manual, and automated based on therole of the user/source component that initiated the workflow or isassociated with the particular process/task corresponding to the workorder. Another example conditional policy/rule is “if (CI-info) then(task); “recently changed”, (M); “error”, (S); “composite”, (A)” whichsets the automation level based on the context information (CI-info)indicating that the context of the process/task has either recentlychanged, has experienced an error condition, or is a composite (made upof two or more parts)

A workflow system may keep a historical record of actions taken in orderto prevent endless loops, or to adapt to changing conditions. Thishistorical information would reflect the state of the system and couldbe used to modify future system behavior. A stateful conditionalautomation rule may be of an “if-then” form where the “if” conditionrelies on state information. An example may be “if (prior automationcount) >3 then escalate one level.”

A goal policy/rule format may define an end-state, but not necessarilyhow to attain the end state. A goal policy/rule format may be of thetype “if (policy conflict) then escalate to Manual.” This policy/rulestates that the end-state should be a manual automation level if apolicy conflict is detected, but does not state how to change theautomation level to the manual state, e.g., upgrading/downgrading ormaintaining the current automation level setting.

A combination of these various rules may be applied to variousattributes of the work order, the context information, and the stateinformation and the results combined to generate a final determinationas to an appropriate level of automation for the particular process/taskcorresponding to the work order. Various ways of combining the resultsof the application of these automation rules may be used withoutdeparting from the spirit and scope of the illustrative embodiments. Forexample, a majority rule may be utilized, a highest level of automation(where highest is closer to full automation) may be selected from thevarious results, a lowest level of automation (where lowest is closer tofill manual execution) may be selected from the various results, aweighting of different automation rules may be used so that a combinedscore may be generated and the score compared to one or more thresholdsindicates whether the automation level attribute should be maintained,upgraded, or downgraded and by how much, etc.

Based on the application of the automation rules to the variousattributes of the work order and the context/status information, the ALE350 may select an automation level modification plan to be implemented.For example, the automation level modification plan may comprise one of:

A) do not change the automation level attribute selected by the sourcecomponent that initiated the workflow;

B) upgrade the automation level attribute (delegate the process/task);

C) downgrade the automation level attribute (escalate the process/task);or

D) set an appropriate level of automation to a particular automationlevel attribute setting.

Once an automation level modification plan has been selected by the ALE350 based on the application of the automation policies/rules defined inthe rules database 360, the ALE 350 may either initiate transmission ofcommands to appropriate components to implement the workflow inaccordance with the automation level modification plan, or may returnthe automation level modification plan to the source component 305 forimplementation. As a result, the level of automation used to implementthe various processes/tasks of the workflow is adapted to the currentcontext/state and is brought into compliance with the establishedautomation policies/rules. As a result, the level of automation may bemade flexible within the system so as to achieve a balance of efficiencydue to automation and security/reduction of risk associated with manualmonitoring/implementation of operations.

FIG. 4 is an example diagram illustrating the operation of the elementsof FIG. 3 with regard to a workload submitted from a source component inaccordance with one illustrative embodiment. As shown in FIG. 4, asource component 410, either automatically or at the direction of a user420, may generate a work order 415 that identifies the work to be doneand what elements of one or more systems are to be controlled, i.e. thework order 415 defines what is to be performed using one or more systemsof one or more organizations. The work order 415 may have an associatedrole attribute that identifies the role of the initiator of the workorder 415. This role may be general, such as “human” or “process”, ormay be more specific and may specify a particular seniority or rankingof the user/system/application that is the initiator of the work order415, e.g., “administrator,” “end user,” “operating system”, “securityapplication” or the like. Any type of role designation may be usedwithout departing from the spirit and scope of the illustrativeembodiments. The role designation may be manually or automaticallyassigned to the work order 415 based on the initiation of the work order415 such that if a particular user initiates the work order 415, forexample, and the user's profile has a particular role attribute, thatrole attribute may be automatically attached to the work order 415 inthe role attribute of the work order 415.

The work order 415 is provided to a workflow management system 440 whichmay interface with the flexible automation workflow management engine300 of the illustrative embodiments. The workflow management system 440may map the work order 415 to a workflow 430 and transmit the workflow430 along with a request 450, having the gathered context/stateinformation of the system(s) associated with the workflow 430, to theflexible automation workflow management engine 300.

That is, the context/state information may be supplied to the tasksequencer by the workflow management system 440. The workflow managementsystem 440 may query and gather the context/state information beforeforwarding the request 450 to the task sequencer 330.

The task sequencer 330 applies task templates to the workflow 430 togenerate a one or more task(s) 460 which are provided to the AEE 340along with the context/state information 470 obtained in the request450. The task(s) 460 may be provided as data structures defining thetask(s) that need to be accomplished as part of the workflow and theparticular ordering of these task(s) within the workflow. The AEE 340invokes the ALE 350 which applies automation policies/rules from therules database 360 to the task(s) 460 and context/state information 470to determine a workflow automation level modification plan 480 that isreturned to the AEE 340 specifying one or more modification operationsto modify the level of automation associated with the task(s) 460. TheAEE 340 returns the plan 480 to the task sequencer 330 which may thenautomatically implement the plan and initiate control of the performanceof the task corresponding to the task(s) 460 directly (as illustrated bythe dashed box) or may return the automation level setting for the taskto the source component 410 for implementation. As shown in the dashedbox in FIG. 4, the levels of automation in this example may be a manualprocess 490, a semi-automated process 492 involving user interactionwith a user interface (UI) that in turn works with an operationsmanagement program (OMP), or an automated process 494 in which anapplication programming interface (API) is used to interface between thesource component 410 and the operations management program (OMP) toperform the corresponding task automatically.

To better understand the flexible automation operations of theillustrative embodiments, it is first helpful to consider a workflowexample such as illustrated in FIG. 5. FIG. 5 is an illustration of anexample of a repetitive workflow that a skilled worker might perform.The workflow includes four steps: (1) Gather Information, (2) AnalyzeInformation, (3) Plan one or more courses of action based on Analysis ofInformation and (4) Execute a selected the course of action. Applyingthis illustration to the illustrative embodiments, one can see that theskilled worker needs to interface with the information technologysystem. The step identified “assume role” represents the tasks that theskilled worker completes in order to pass identification andauthorization checks. This is often referred to as a “login process”.The step identified as “organize work” represents the tasks that theskilled worker completes in order to prepare for performing the skilledtasks in the workflow (Gather, Analyze, Plan, Execute). This step mightinclude setting the default level of automation, reviewing previoussystem history, or signaling to the system that the skilled worker isready for work.

In this example, various levels of automation will be utilized. Level 0correlates to a completely manually implemented task. Level 1 correlatesto a manual process with user interface (U1) assistance for providingvisualization and prompting for user inputs. Level 2 correlates to asemi-automatic process with UI assistance by providing Launch in Context(LIC) to underlying operations management programs (OMPs), where theOMPs are software mechanism that interface to resources that are to bemanaged. Level 3 correlates to a primarily automated process with directsoftware integration to underlying operations management programs(OMPs), with or without user awareness or control.

As shown in FIG. 5, initially, a user assumes the user's role 510 (e.g.,administrator, analyst, operator, etc.) and organizes the work to beperformed through a semi-automated process in which the user interactswith an OMP via a user interface (UI) to generate a work order that ismapped to a workflow 500 (the user interaction is illustrated as beingat automation levels 1, 2). The workflow 500 is provided to themechanisms of the illustrative embodiments which analyze the tasks502-508 of the workflow 500, compare them to predefined task templates,and generate work orders 510-516 for the various tasks. The illustrativeembodiments then take the next task in the workflow 500, e.g., task 502,and apply automation policies/rules to the work order 510 to determine alevel of automation to be used with the task 502 corresponding to thework order 510 (element 550). In the depicted example, the automationpolicy comprises three rules: 1) if role=human, then maintainedpre-determined automation level; 2) if role=program, then set automationlevel to 3; and 3) if role=program, and error=yes, then escalateautomation level (towards manual).

The level of automation may be one of a plurality of differentautomation levels ranging from a fully manual level to a fully automaticlevel. For example, in the depicted example, the automation level may beone of manual 520 requiring human intervention to cause the task to becompleted correctly, semi-automatic 530 in which a user interface withautomated mechanisms and monitors/controls the operation of theseautomated mechanisms, e.g., a user using a user interface (UI)interfaces with an operations management program (OMP) to perform thetask 502-508, or automatic 530 in which APIs are used to automaticallyinterface and initiate operations by the OMP to perform the task502-508.

This determination of automation level is performed for each work order510-516 either simultaneously or in succession. The determination isbased on the application of automation rules to the attributes of thework order 510-516 as well as the context/state information of thesystems that are involved in performing the workload 500. The results ofthe determinations are then utilized to update the automation levelattributes of the tasks 502-508 to cause these tasks to be performedaccording to the corresponding dynamically generated automation level,

Thus, the illustrative embodiments provide mechanisms for flexibledetermination of an automation level for processes/tasks of a workflowbased on the attributes associated with the particular processes/tasksand the current context/state of the environment in which theprocesses/tasks are to be executed. The mechanisms of the illustrativeembodiments apply automation policies/rules to the attributes of thetasks/processes of the workflow as well as the context/state informationto determine an appropriate level of automation for the task/processunder the current context/state of the environment. In some illustrativeembodiments, this is essentially a determination of the level of riskthat a negative result will be generated by execution of theprocess/task in an automated fashion. In other words, the application ofthe automation policies/rules essentially determines that, under thecurrent conditions (as identified by the context/state information),what is the risk that automated execution of a task/process may resultin any of a number of different negative outcomes. If that risk issufficiently high, then more manual intervention is appropriate.However, if that risk is sufficiently low, then a more automatedapproach is warranted so as to achieve greater efficiency in theexecution of the task. The measure of risk is made by the application ofthe automation rules and the sufficiency or a predicted risk isdetermined in comparison to one or more thresholds.

FIG. 6 is a flowchart outlining an example operation for performing aflexible automation determination for a workflow in accordance with oneillustrative embodiment. The operation outlined in FIG. 6 may beimplemented, for example, by a flexible automation workflow managementengine, such as mechanism 300 in FIG. 3.

As shown in FIG. 6, the operation starts by receiving a workflow and arequest with context/state information for the environment in which theworkflow is to be executed (step 610). Tasks in the workflow areidentified (step 620). Automation rules are applied to the taskattributes and context/state info to determine various appropriatelevels of automation for the various tasks associated with the workorder(s) (step 630). An automation level modification plan is generatedbased on the results of the determination of appropriate automationlevels for the tasks as determined from the application from theautomate rules (step 640). Automation level attributes ofprocesses/tasks are modified based on the automation level modificationplan (step 650). The various processes/tasks of the workflow are thenexecuted in the environment using the automation levels determined inaccordance with the operation (step 660). The operation then terminates.

As noted above, it should be appreciated that the illustrativeembodiments may take the form of an entirely hardware embodiment, anentirely software embodiment or an embodiment containing both hardwareand software elements. In one example embodiment, the mechanisms of theillustrative embodiments are implemented in software or program code,which includes but is not limited to firmware, resident software,microcode, etc.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution.

Input/output or I/O devices (including but not limited to keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening I/O controllers. Network adapters mayalso be coupled to the system to enable the data processing system tobecome coupled to other data processing systems or remote printers orstorage devices through intervening private or public networks. Modems,cable modems and Ethernet cards are just a few of the currentlyavailable types of network adapters.

The description of the present invention has been presented for purposesof illustration and description, and is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the art. Theembodiment was chosen and described in order to best explain theprinciples of the invention, the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

1. A method, in a data processing system, for dynamically determining one or more automation levels for tasks of a workflow, comprising: receiving, from a source component, the workflow in an environment in which the workflow is to be performed; receiving, from the source component, required context information and state information of the environment in which the workflow is to be performed; identifying two or more tasks and task attributes associated with each task in the two or more tasks in the workflow; applying one or more automation rules to the context information and the state information of the environment as well as the task attributes associated with the each task in the two or more tasks identified from the workflow to generate an individualized automation level setting for each work order of a two or more work orders generated from the two or more tasks in the workflow, wherein applying the one or more automation rules to the context information, the state information, and the task attributes to generate the individualized automation level setting for each of the two or more work orders comprises evaluating the context information and the state information according to conditions specified in the one or more automation rules and setting each individualized automation level setting to a first setting based on the context information and the state information satisfying the conditions specified in the one or more automation rules and setting each individualized automation level setting to a second setting based on the context information and the state information not satisfying the conditions specified in the one or more automation rules; and performing the each of work order of the two or more work orders in the environment in which the workflow is to be performed in accordance with its associated individualized automation level setting, wherein the individualized automation level setting specifies a degree of automation to be used when performing the work order.
 2. The method of claim 1, wherein applying the one or more automation rules comprises at least one of: maintaining the individualized automation level setting for each work order in the two or more work orders; increasing the individualized automation level setting for one or more work orders in the two or more work orders to thereby increase an amount of automation used to perform the one or more work orders; or decreasing the individualized automation level setting for the one or more work order in the two or more work orders to reduce an amount of automation used to perform the one or more work orders and increase an amount of manual intervention in the performance of the one or more work orders.
 3. The method of claim 1, wherein the degree of automation is within a range of automation having a first bound corresponding to a fully automatic automation level setting and a second bound corresponding to a fully manual automation level setting.
 4. The method of claim 1, wherein at least two of the two or more work orders have different associated automation levels settings.
 5. The method of claim 1, wherein generating the two or more work orders from the two or more tasks in the workflow comprises: comparing the each task within the two or more tasks in the workflow to a set of predefined task templates in order to identify a task template associated with the task utilizing the identified two or more task templates for the corresponding two or more tasks to thereby define the workflow based on the identified two or more task templates from the set of predefined task templates; and converting the each task in the identified two or more task templates to a work order thereby creating the two or more work orders that conform to the identified two or more task templates.
 6. The method of claim 1, wherein the context information and the state information comprises one or more environmental variables specifying a current state of availability of one or more components of the environment required to perform at least one of the two or more work orders.
 7. The method of claim 1, wherein the one or more automation rules comprise at least one of a declarative automation rule, a simple conditional automation rule, a stateful conditional automation rule, or a goal based automation rule.
 8. The method of claim 1, wherein performing the two or more work orders in the environment in accordance with the individualized automation level settings comprises transmitting a command to a component of the environment to cause the component to operate in accordance with the individualized automation level setting corresponding to the component.
 9. (canceled)
 10. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive, from a source component, a workflow in an environment in which the workflow is to be performed; receive, from the source component, required context information and state information of the environment in which the workflow is to be performed; identify two or more tasks and associated task attributes associated with each task in the two or more tasks in the workflow; apply one or more automation rules to the context information and the state information of the environment as well as the task attributes associated with the each task in the two or more tasks identified from the workflow to generate an individualized automation level setting for each work order of two or more work orders generated from the two or more tasks in the workflow, wherein the computer readable program causes the computing device to apply the one or more automation rules to the context information, the state information, and the task attributes to generate the individualized automation level setting for each of the two or more work orders comprises evaluating the context information and the state information according to conditions specified in the one or more automation rules and setting each individualized automation level setting to a first setting based on the context information and the state information satisfying the conditions specified in the one or more automation rules and setting each individualized automation level setting to a second setting based on the context information and the state information not satisfying the conditions specified in the one or more automation rules; and perform the each work order of the two or more work orders in the environment in which the workflow is to be performed in accordance with its associated individualized automation level setting, wherein the individualized automation level setting specifies a degree of automation to be used when performing the work order.
 11. The computer program product of claim 10, wherein the computer readable program causes the computing device to apply the one or more automation rules by at least one of: maintaining the individualized automation level setting for each work order in the two or more work orders; increasing the individualized automation level setting for one or more work orders in the two or more work orders to thereby increase an amount of automation used to perform the one or more work orders; or decreasing the individualized automation level setting for the one or more work order in the two or more work orders to reduce an amount of automation used to perform the one or more work orders and increase an amount of manual intervention in the performance of the one or more work orders.
 12. The computer program product of claim 10, wherein the degree of automation is within a range of automation having a first bound corresponding to a fully automatic automation level setting and a second bound corresponding to a fully manual automation level setting.
 13. The computer program product of claim 10, wherein at least two of the two or more work orders have different associated automation levels settings.
 14. The computer program product of claim 10, wherein the computer readable program causes the computing device to generate the two or more work orders from the two or more tasks in the workflow by: comparing the each task within the two or more tasks in the workflow to a set of predefined task templates in order to identify a task template associated with the task utilizing the identified two or more task templates for the corresponding two or more tasks to thereby define the workflow based on the identified two or more task templates from the set of predefined task templates; and converting the each task in the identified two or more task templates to a work order thereby creating the two or more work orders that conform to the identified two or more task templates.
 15. The computer program product of claim 10, wherein the context information and the state information comprises one or more environmental variables specifying a current state of availability of one or more components of the environment required to perform at least one of the two or more work orders.
 16. The computer program product of claim 10, wherein the one or more automation rules comprise at least one of a declarative automation rule, a simple conditional automation rule, a stateful conditional automation rule, or a goal based automation rule.
 17. The computer program product of claim 10, wherein the computer readable program causes the computing device to perform the two or more work orders in the environment in accordance with the individualized automation level settings comprises transmitting a command to a component of the environment to cause the component to operate in accordance with the individualized automation level setting corresponding to the component.
 18. (canceled)
 19. An apparatus, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, from a source component, a workflow in an environment in which the workflow is to be performed; receive, from the source component, required context information and state information of the environment in which the workflow is to be performed; identify two or more tasks and associated task attributes associated with each task in the two or more tasks in the workflow; apply one or more automation rules to the context information and the state information of the environment as well as the task attributes associated with the each task in the two or more tasks identified from the workflow to generate an individualized automation level setting for each work order of two or more work orders generated from the two or more tasks in the workflow, wherein the instructions cause the processor to apply the one or more automation rules to the context information, the state information, and the task attributes to generate the individualized automation level setting for each of the two or more work orders comprises evaluating the context information and the state information according to conditions specified in the one or more automation rules and setting each individualized automation level setting to a first setting based on the context information and the state information satisfying the conditions specified in the one or more automation rules and setting each individualized automation level setting to a second setting based on the context information and the state information not satisfying the conditions specified in the one or more automation rules; and perform the each work order of the two or more work orders in the environment in which the workflow is to be performed in accordance with its associated individualized automation level setting, wherein the individualized automation level setting specifies a degree of automation to be used when performing the work order.
 20. The apparatus of claim 19, wherein the instructions cause the processor to apply the one or more automation rules by at least one of: maintaining the individualized automation level setting for each work order in the two or more work orders; increasing the individualized automation level setting for one or more work orders in the two or more work orders to thereby increase an amount of automation used to perform the one or more work orders; or decreasing the individualized automation level setting for the one or more work order in the two or more work orders to reduce an amount of automation used to perform the one or more work orders and increase an amount of manual intervention in the performance of the one or more work orders.
 21. The apparatus of claim 19, wherein the degree of automation is within a range of automation having a first bound corresponding to a fully automatic automation level setting and a second bound corresponding to a fully manual automation level setting.
 22. The apparatus of claim 19, wherein at least two of the two or more work orders have different associated automation levels settings.
 23. The apparatus of claim 19, wherein the instructions cause the processor to generate the two or more wok orders from the two or more tasks in the workflow by: comparing the each task within the two or more tasks in the workflow to a set of predefined task templates in order to identify a task template associated with the task utilizing the identified two or more task templates for the corresponding two or more tasks to thereby define the workflow based on the identified two or more task templates from the set of redefined task templates; and converting the each task in the identified two or more task templates to a work order thereby creating the two or more work orders that conform to the identified two or more task templates.
 24. The apparatus of claim 19, wherein the context information and the state information comprises one or more environmental variables specifying a current state of availability of one or more components of the environment required to perform at least one of the two or more work orders.
 25. The apparatus of claim 19, wherein the one or more automation rules comprise at least one of a declarative automation rule, a simple conditional automation rule, a stateful conditional automation rule, or a goal based automation rule.
 26. The apparatus of claim 19, wherein the instructions cause the processor to perform the two or more work orders in the environment in accordance with the individualized automation level settings comprises transmitting a command to a component of the environment to cause the component to operate in accordance with the individualized automation level setting corresponding to the component. 